MARKETING
How to Use Header Bidding
Despite the technology involved in the adtech space, there are still many inefficiencies and unfair practices that need to be ironed out. Header bidding is a solution that brings publishers and advertisers together.
What Is Header Bidding?
Header bidding is a process where many advertisers simultaneously bid (in real-time) in a digital auction to win ad space on your website. This auction occurs outside your primary ad server every time your pages load or whenever an ad unit refreshes.
For publishers, the primary advantage is it helps ensure you get the best deals on your ad space. To do this, you must ensure that you reach out to supply-side platforms (SSPs) and other demand partners to ensure you have many advertisers to bid on your inventory.
Header bidding is a more refined way of auctioning off your ad inventory. While it may be a bit more complex to implement than traditional methods (like waterfall bidding), it has many advantages that make it worth the hassle.
How Header Bidding Works
Here’s how the whole process play out when a visitor lands on a publisher’s page:
- A visitor clicks a link that takes them to a web page
- As the page loads, the short string of JavaScript in the page’s header makes a call to your demand partners or ad networks
- Each demand partner places a bid on the publisher’s ad inventory
- The winning bid is directed to the publisher’s ad server
- The publisher’s ad server then connects the user to the advertiser’s server and displays the winning ad
The process may involve several steps, but it takes less than a second from start to finish.
Header Bidding Vs. Waterfall Bidding
One of the most popular methods of buying and selling ad space was waterfall bidding. It has worked pretty well for the past few years, and some publishers are still reluctant to move away from it to embrace header bidding.
The question, however, is which is better: header bidding or waterfall bidding?
To properly understand why it is your better option, we need to briefly look at what waterfall bidding is and its pros and cons.
What Is Waterfall Bidding, and How Does It Work?
Waterfall bidding is one of the earliest forms of programmatic bidding.
Waterfall bidding is an old-school way of ad serving in which publishers set a floor price for their ad space. The publisher sets the priority for each advertiser or ad network they’re connected to.
When selling ad impressions using the waterfall bidding process, inventory is offered to advertisers at a fixed minimum price per impression. The first ad network to bid at that price gets the slot.
Another important aspect of waterfall bidding is that the bidders don’t get to bid randomly. Networks that rank higher, thanks to higher historical yield, get dibs on bidding.
In a sense, waterfall bidding isn’t accurate bidding at all.
The most significant disadvantage of waterfall bidding is that the price you sell your inventory at doesn’t necessarily reflect its true value.
Ad space that remains unsold is passed on to the next ad exchange, determined by size, not the amount of the bid. The process goes on until the inventory is sold. It’s from this cascading nature of passing down inventory that the waterfall method gets its name.
Unfortunately for publishers, this means if the runner-up advertiser was willing to pay more, the publisher misses out on getting more revenue.
9 Reasons You Should Use Header Bidding
You’ve probably noticed a few advantages that header bidding has (for both publishers and advertisers) over other methods of auctioning off ad space.
Some of these benefits include:
1. Header Building Gives Publishers Access to More Advertisers
For publishers, a significant advantage of header bidding is it allows you to expand and diversify the advertisers on your site. It ensures that you’re not reliant on a small set of advertisers. Doing so helps increase your business’ resilience and adaptability.
2. Fair Bidding
One of the biggest advantages for advertisers is that it levels the playing field. That’s because no advertiser has an advantage. All bids are placed fairly, and the highest bidder wins, no matter who they are (and even if they use AdEx).
3. Header Building Improves Auction Efficiency
This type of bidding utilizes real-time pricing instead of the historical pricing used by other ad auction models. This makes it faster and more efficient.
4. Header Bidding Gives You More Control
For publishers, one of the main advantages is it gives you more control over the sources that can participate in the bidding process. As a publisher, you retain control over your site.
5. Increased Revenue
Another reason publishers like header bidding is the increased ad revenue. Not only can you charge more for your premium inventory, but you are also assured that the highest bidder wins every time.
6. Improved Ad Quality
Thanks to the increased competition, advertisers work hard to ensure their ads are high quality and more relevant to a publisher’s audience. Improved ad quality helps ensure a better user experience (UX.)
7. Improved Yield
With header bidding, you rely less on a single supply-side platform. As a result, your overall yield increases due to smarter allocation of impressions and increased fill rate.
8. Increased Fill Rates
One main reason you should use header bidding is that it exposes you to more advertisers. This has the huge advantage of increasing the chances of publishers filling all their ad slots.
9. Better Transparency
Advertisers enjoy the improved transparency that header bidding affords. They have access to all the publisher’s inventory, and thus know what’s available and how much it can cost them. This transparency helps advertisers make informed bidding decisions.
Header bidding has so many advantages for both publishers and advertisers, it’s undoubtedly worth the effort to implement it.
What Are the Drawbacks of Header Bidding?
While this type of bidding might seem like the perfect solution for both advertisers and publishers to maximize their returns, it does have its drawbacks. Here are the main ones:
Increased Latency
To run header bidding, publishers have to add a script to their site, which can slow down page load speed, resulting in a poor user experience. Another caveat is that the more advertisers that bid on your inventory, the more the page latency is affected.
You can mitigate these by following website optimization best practices to ensure your pages load faster.
Increased Management Overheads
Once you’ve set up header bidding, it requires close management to ensure it performs well. Besides ensuring that your code is working well for all your partners, adjusting bids, timeouts, and several other tasks are required to keep your header bidding optimized.
Infrastructure Costs
Implementing this bidding style can lead to increased infrastructure costs for SSPs and demand-side platforms (DSPs). One reason for this is the increased load on their servers. Another reason is the required tools and personnel needed to run it.
Header bidding may have its drawbacks, but overall, the pros definitely outweigh the cons.
How to Implement Header Bidding
Implementing header bidding for publishers can be a complicated process. Setting it up is tedious as it may require you to develop countless line items of ad inventory. As said, this can have an impact on your page load speed. The consequences are poor UX for both advertisers and website visitors.
Thankfully, there are a couple of solutions for that: wrappers and server-side.
Header Bidding Wrappers
Header bidding wrappers are code containers that help ensure all auctions start simultaneously and end on time. Wrappers also ensure ads load asynchronously. This means the page’s content can load before the ads, ensuring your website latency doesn’t impact visitors
Server-Side Header Bidding
Another solution is to implement server-side header bidding.
Traditional header bidding takes place client-side (also called browser-side), meaning it depends on the browser to handle individual networks’ requests. Of course, this can put a strain on resources; something header wrappers can help address.
If many networks access the header wrapper, it triggers several JavaScript processes that make site load speed suffer.
One way to solve that problem is to limit the number of advertisers that can bid for your inventory. However, that defeats the purpose of header bidding, as you want as many advertisers as possible to participate.
Server-side header building is a solution to this problem. Server-side header bidding takes the bidding process off your browser and moves it to an external server.
To do this, you must embed code on the back-end of your website. This way, all the heavy work is transferred from your browser to your ad server. As a result, your browser can focus on the one thing it’s meant to do: serve your website visitors with content.
One of the most significant advantages of server-side is that it helps improve page load times. It also helps ensure a more efficient bidding process.
Conclusion
Whether you’re a publisher or advertiser, you should consider a header bidding strategy.
For advertisers, header bidding levels the playing field by allowing everyone to bid fairly, no matter the ad network’s size.
Publishers ensure their ad inventory sells for what it’s worth. Your primary task is to drive traffic to your website and let the bidding code do the heavy lifting of monetizing your website. With header bidding, you won’t leave money on the table, which is a win-win for everyone involved.
If you need help implementing a header bidding strategy (or even a holistic campaign that incorporates other digital ad strategies), let our agency know. Our team of experts can help!
Have you tried header bidding as a publisher or advertiser?
What was your experience with it?
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MARKETING
YouTube Ad Specs, Sizes, and Examples [2024 Update]
Introduction
With billions of users each month, YouTube is the world’s second largest search engine and top website for video content. This makes it a great place for advertising. To succeed, advertisers need to follow the correct YouTube ad specifications. These rules help your ad reach more viewers, increasing the chance of gaining new customers and boosting brand awareness.
Types of YouTube Ads
Video Ads
- Description: These play before, during, or after a YouTube video on computers or mobile devices.
- Types:
- In-stream ads: Can be skippable or non-skippable.
- Bumper ads: Non-skippable, short ads that play before, during, or after a video.
Display Ads
- Description: These appear in different spots on YouTube and usually use text or static images.
- Note: YouTube does not support display image ads directly on its app, but these can be targeted to YouTube.com through Google Display Network (GDN).
Companion Banners
- Description: Appears to the right of the YouTube player on desktop.
- Requirement: Must be purchased alongside In-stream ads, Bumper ads, or In-feed ads.
In-feed Ads
- Description: Resemble videos with images, headlines, and text. They link to a public or unlisted YouTube video.
Outstream Ads
- Description: Mobile-only video ads that play outside of YouTube, on websites and apps within the Google video partner network.
Masthead Ads
- Description: Premium, high-visibility banner ads displayed at the top of the YouTube homepage for both desktop and mobile users.
YouTube Ad Specs by Type
Skippable In-stream Video Ads
- Placement: Before, during, or after a YouTube video.
- Resolution:
- Horizontal: 1920 x 1080px
- Vertical: 1080 x 1920px
- Square: 1080 x 1080px
- Aspect Ratio:
- Horizontal: 16:9
- Vertical: 9:16
- Square: 1:1
- Length:
- Awareness: 15-20 seconds
- Consideration: 2-3 minutes
- Action: 15-20 seconds
Non-skippable In-stream Video Ads
- Description: Must be watched completely before the main video.
- Length: 15 seconds (or 20 seconds in certain markets).
- Resolution:
- Horizontal: 1920 x 1080px
- Vertical: 1080 x 1920px
- Square: 1080 x 1080px
- Aspect Ratio:
- Horizontal: 16:9
- Vertical: 9:16
- Square: 1:1
Bumper Ads
- Length: Maximum 6 seconds.
- File Format: MP4, Quicktime, AVI, ASF, Windows Media, or MPEG.
- Resolution:
- Horizontal: 640 x 360px
- Vertical: 480 x 360px
In-feed Ads
- Description: Show alongside YouTube content, like search results or the Home feed.
- Resolution:
- Horizontal: 1920 x 1080px
- Vertical: 1080 x 1920px
- Square: 1080 x 1080px
- Aspect Ratio:
- Horizontal: 16:9
- Square: 1:1
- Length:
- Awareness: 15-20 seconds
- Consideration: 2-3 minutes
- Headline/Description:
- Headline: Up to 2 lines, 40 characters per line
- Description: Up to 2 lines, 35 characters per line
Display Ads
- Description: Static images or animated media that appear on YouTube next to video suggestions, in search results, or on the homepage.
- Image Size: 300×60 pixels.
- File Type: GIF, JPG, PNG.
- File Size: Max 150KB.
- Max Animation Length: 30 seconds.
Outstream Ads
- Description: Mobile-only video ads that appear on websites and apps within the Google video partner network, not on YouTube itself.
- Logo Specs:
- Square: 1:1 (200 x 200px).
- File Type: JPG, GIF, PNG.
- Max Size: 200KB.
Masthead Ads
- Description: High-visibility ads at the top of the YouTube homepage.
- Resolution: 1920 x 1080 or higher.
- File Type: JPG or PNG (without transparency).
Conclusion
YouTube offers a variety of ad formats to reach audiences effectively in 2024. Whether you want to build brand awareness, drive conversions, or target specific demographics, YouTube provides a dynamic platform for your advertising needs. Always follow Google’s advertising policies and the technical ad specs to ensure your ads perform their best. Ready to start using YouTube ads? Contact us today to get started!
MARKETING
Why We Are Always ‘Clicking to Buy’, According to Psychologists
Amazon pillows.
MARKETING
A deeper dive into data, personalization and Copilots
Salesforce launched a collection of new, generative AI-related products at Connections in Chicago this week. They included new Einstein Copilots for marketers and merchants and Einstein Personalization.
To better understand, not only the potential impact of the new products, but the evolving Salesforce architecture, we sat down with Bobby Jania, CMO, Marketing Cloud.
Dig deeper: Salesforce piles on the Einstein Copilots
Salesforce’s evolving architecture
It’s hard to deny that Salesforce likes coming up with new names for platforms and products (what happened to Customer 360?) and this can sometimes make the observer wonder if something is brand new, or old but with a brand new name. In particular, what exactly is Einstein 1 and how is it related to Salesforce Data Cloud?
“Data Cloud is built on the Einstein 1 platform,” Jania explained. “The Einstein 1 platform is our entire Salesforce platform and that includes products like Sales Cloud, Service Cloud — that it includes the original idea of Salesforce not just being in the cloud, but being multi-tenancy.”
Data Cloud — not an acquisition, of course — was built natively on that platform. It was the first product built on Hyperforce, Salesforce’s new cloud infrastructure architecture. “Since Data Cloud was on what we now call the Einstein 1 platform from Day One, it has always natively connected to, and been able to read anything in Sales Cloud, Service Cloud [and so on]. On top of that, we can now bring in, not only structured but unstructured data.”
That’s a significant progression from the position, several years ago, when Salesforce had stitched together a platform around various acquisitions (ExactTarget, for example) that didn’t necessarily talk to each other.
“At times, what we would do is have a kind of behind-the-scenes flow where data from one product could be moved into another product,” said Jania, “but in many of those cases the data would then be in both, whereas now the data is in Data Cloud. Tableau will run natively off Data Cloud; Commerce Cloud, Service Cloud, Marketing Cloud — they’re all going to the same operational customer profile.” They’re not copying the data from Data Cloud, Jania confirmed.
Another thing to know is tit’s possible for Salesforce customers to import their own datasets into Data Cloud. “We wanted to create a federated data model,” said Jania. “If you’re using Snowflake, for example, we more or less virtually sit on your data lake. The value we add is that we will look at all your data and help you form these operational customer profiles.”
Let’s learn more about Einstein Copilot
“Copilot means that I have an assistant with me in the tool where I need to be working that contextually knows what I am trying to do and helps me at every step of the process,” Jania said.
For marketers, this might begin with a campaign brief developed with Copilot’s assistance, the identification of an audience based on the brief, and then the development of email or other content. “What’s really cool is the idea of Einstein Studio where our customers will create actions [for Copilot] that we hadn’t even thought about.”
Here’s a key insight (back to nomenclature). We reported on Copilot for markets, Copilot for merchants, Copilot for shoppers. It turns out, however, that there is just one Copilot, Einstein Copilot, and these are use cases. “There’s just one Copilot, we just add these for a little clarity; we’re going to talk about marketing use cases, about shoppers’ use cases. These are actions for the marketing use cases we built out of the box; you can build your own.”
It’s surely going to take a little time for marketers to learn to work easily with Copilot. “There’s always time for adoption,” Jania agreed. “What is directly connected with this is, this is my ninth Connections and this one has the most hands-on training that I’ve seen since 2014 — and a lot of that is getting people using Data Cloud, using these tools rather than just being given a demo.”
What’s new about Einstein Personalization
Salesforce Einstein has been around since 2016 and many of the use cases seem to have involved personalization in various forms. What’s new?
“Einstein Personalization is a real-time decision engine and it’s going to choose next-best-action, next-best-offer. What is new is that it’s a service now that runs natively on top of Data Cloud.” A lot of real-time decision engines need their own set of data that might actually be a subset of data. “Einstein Personalization is going to look holistically at a customer and recommend a next-best-action that could be natively surfaced in Service Cloud, Sales Cloud or Marketing Cloud.”
Finally, trust
One feature of the presentations at Connections was the reassurance that, although public LLMs like ChatGPT could be selected for application to customer data, none of that data would be retained by the LLMs. Is this just a matter of written agreements? No, not just that, said Jania.
“In the Einstein Trust Layer, all of the data, when it connects to an LLM, runs through our gateway. If there was a prompt that had personally identifiable information — a credit card number, an email address — at a mimum, all that is stripped out. The LLMs do not store the output; we store the output for auditing back in Salesforce. Any output that comes back through our gateway is logged in our system; it runs through a toxicity model; and only at the end do we put PII data back into the answer. There are real pieces beyond a handshake that this data is safe.”
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